The document defines and discusses the Dirac delta function in 4 sentences: 1) The Dirac delta function can be defined as the limit of a shrinking rectangular pulse with increasing height such that the area under the curve remains 1. 2) Alternatively, it can be defined as the derivative of the Heaviside step function, which is infinite only at the origin and integrates to 1 from negative to positive infinity. 3) The Dirac delta function can also be defined as the Fourier transform of a pure sine or cosine wave, which results in a single peak. 4) It can represent the density of a point mass, being zero everywhere except at the origin where it is infinite but integrates to the total

1. Dirac delta function, by Dr Colton
Physics 471 – Optics
Definitions
1. Definition as limit. The Dirac delta function can be thought of as a rectangular pulse that grows
narrower and narrower while simultaneously growing larger and larger.
rect(x, b) =
0
( ) lim rect( , )
b
x x bδ
→
=
Note that the integral of the delta function is the area under the curve, and has been held constant at 1
throughout the limit process.
1)( =∫
∞
∞−
xδ area of delta function
Shifting the origin. Just as a parabola can be shifted away from the origin by writing y = (x – x0)2
instead
of just y = x2
, any function can be shifted by plugging in x – x0 in place of its usual argument x.
δ(x - x0) =
Shifting the position of the peak doesn’t affect the total area if the integral is taken from –∞ to ∞.
1)( 0 =−∫
∞
∞−
xxδ area of delta function
Disclaimer: Mathematicians may object that the Dirac delta function defined this way (or any other way,
for that matter) is not a real function. That is true, but physicists recognize that for all practical purposes
you really can just think of the delta function as a very large and narrow peak with an area of 1.
Delta functions – pg 1
x
y
width = b
height = 1/b
(so total area = 1)
x
y
x0
x
y
(infinitely high,
infinitely narrow)
definition of delta function

2. 2. Definition as derivative of step function. The step function, also called the “Heaviside step function” is
usually defined like this:*
H(x) = 0 for x < 0,
H(x) = 0.5 for x = 0
H(x) = 1 for x > 0
It’s a function whose only feature is a step up from 0 to 1, at the origin:
What’s the derivative of this function? Well, the slope is zero for x < 0 and the slope is zero for x > 0.
What about right at the origin? The slope is infinite! So the derivative of this function is a function which
is zero everywhere except at the origin, where it’s infinite. Also, the integral of that derivative function
from –∞ to ∞ must be 1! (Think of the Fundamental Theorem of Calculus: the integral of the derivative
function will be H(∞) – H(–∞), which is 1.) An infinite peak at the origin whose integral is 1? Sound
familiar? Therefore δ(x) can also be defined as the derivative of the step function.
3. Definition as Fourier transform. We’ve seen that taking the Fourier transform of a function gives you
the frequency components of the function. What about taking the Fourier transform of a pure sine or
cosine wave oscillating at ω0? There is only one frequency component, so the Fourier transform must be
a single, very large peak at ω0 (or possibly two peaks, one at ω0 and one at –ω0). A delta function!
4. Definition as density. What’s the density of a 1 kg point mass located at the origin? Well, it’s a
function that must be zero everywhere except at the origin—and it must be infinitely large at the origin
because for a mass that truly occupies only a single point, the mass must have been infinitely compressed.
How about the integral? The volume integral of the density must give you the mass, which is 1 kg. A
function that is zero everywhere except at the origin, and has an integral equal to 1? Sounds like the delta
function again!
More precisely, this would be a three-dimensional analog to the regular delta function δ(x), because the
density must be integrated over three dimensions in order to give the mass. This is sometimes written δ(r)
or as δ 3
(r):
δ 3
(r) = δ(x) δ(y) δ(z)
Properties
*
This is also sometimes called the “theta function” or “Heaviside theta function” and Θ(x) is sometimes used as the
function symbol. (Θ = capital theta.)
Delta functions – pg 2
x
H
1

3. 1. Integral. One of the most important properties of the delta function has already been mentioned: it
integrates to 1.
2. Sifting property. When a delta function δ(x – x0) multiplies another function f(x), the product must be
zero everywhere except at the location of the infinite peak, x0. At that location, the product is infinite like
the delta function, but it might be a “larger” or “smaller” infinity, depending on whether the value of f(x)
at that point is larger or smaller than 1. In other words, the area of the product function is not necessarily
1 anymore, it is modified by the value of f(x) at the infinite peak. This is called the “sifting property” of
the delta function:
∫
∞
∞−
=− )()()( 00 xfdxxfxxδ
Mathematicians may call the delta function a “functional”, because it is really only well-defined inside
integrals like this, in terms of what it does to other functions. (A “functional” is something that operates
on functions, rather than a “function” which is something that operates on variables.)
3. Symmetry. A few other properties can be readily seen from the definition of the delta function:
a. δ(x) = δ(–x) δ(x) behaves as if it were an even function
b. δ(x – x0) = δ(–(x – x0) ) δ(x – x0) is symmetric about x = x0
4. Linear systems. If a physical system has linear responses and if its response to delta functions
(“impulses”) is known, then in theory the output of this system can be determined for almost any input,
no matter how complex. This rather amazing property of linear systems is a result of the following:
almost any arbitrary function can be decomposed into (or “sampled by”) a linear combination of delta
functions, each weighted appropriately, and each of which produces its own impulse response. Thus, by
application of the superposition principle, the overall response to the arbitrary input can be found by
adding up all of the individual impulse responses.
Fourier Transforms of delta functions
1. A single delta function. The Fourier transform of a single delta function in time can be obtained using
the sifting property and the definition of the F.T.:
{ } 01 1 1
( ) ( )
2 2 2
i t i
FT t t e dt eω ω
δ δ
π π π
∞
×
−∞
= = =∫
Similarly, the Fourier transform of δ(t – t0) is:
{ } )(
00
0
2
1
)(
2
1
)( titi
edtettttFT ωω
π
δ
π
δ =−=− ∫
∞
∞−
{ } 0
2
1
)( 0
ti
ettFT ω
π
δ =−
The Fourier transform has a constant amplitude but a phase that varies linearly with ω.
Another interesting way to define the delta function can be obtained by doing the reverse Fourier
Transform and setting it equal to the original delta function:
Delta functions – pg 3

4. ∫
∞
∞−
−−






=






ω
πππ
ωωω
deeeFT tititi 00
2
1
2
1
2
11
∫
∞
∞−
−−
=− ω
π
δ ω
dett tti )(
0
0
2
1
)( yet another way Dirac delta functions can be
defined
Note: the negative sign in the exponent is optional for this defition, as can be seen by substituting in
ω′ = –ω: the dω becomes –dω′, but the limits of integration are reversed.
2. Finite comb function. A series of equally spaced delta functions, sometimes called the comb function,
is written as:
∑−=
−=
N
Nn
ntttcomb )()( δ where tn = n t0 (note that comb is also a function of N)
One potential use for the comb function might be to perform a sampling operation on another function
(see “Linear systems,” above).
The Fourier transform of the comb function is
{ }
1 1
( ) ( )
2 2
n
N N
i ti t
n
n N n N
FT comb t t t e dt e ωω
δ
π π
∞
=− =−−∞
= − =∑ ∑∫
For example, if N = 1, the Fourier transform is:
{ } ( ) ( ))cos(21
2
1
1
2
1
)1,( 0
00
teeNtcombFT titi
ω
ππ
ωω
+=++== −
For arbitrary N, the Fourier transform is given by
{ } ∑−=
=
N
Nn
ti n
eNtcombFT ω
π2
1
),(
which, after summing the finite series, using Ntot = 2N + 1, and doing lots of algebra, reduces to:
{ }
( )
( )
0
0
sin 21
( ),
sin 22
tot
tot
N t
FT comb t N
t
ω
ωπ
=
That is a periodic function made up of large primary peaks surrounded by secondary peaks that decrease
in amplitude as you move away from the primary peak.
Delta functions – pg 4
x
y
……
t0
Ntot = 2N + 1 total delta functions

5.  6  4  2 2 4 6
 5
5
1 0
1 5
2 0
Notice that the function is periodic and repeats every 2π.
As can be found from L’Hospital’s Rule, the amplitude of the primary peak depends on N:
amplitude = Ntot/sqrt(2π)
The first zero (a measure of the width of the primary peak) is given by
0
2
first zero
totN t
π
ω =
3. Infinite comb function: Using the previous two equations, one can see that in the limit as Ntot → ∞, the
large peaks (like the ones at –2π, 0, and 2π) get infinitely tall and infinitely narrow. They are delta
functions! Thus, the Fourier transform of an infinite comb function in the time domain, is a similar
infinite comb function in the frequency domain.
Delta functions – pg 5
FT(comb) plotted here as a
function of ωt0, for Ntot = 21,
without the 1/sqrt(2π)

6.  6  4  2 2 4 6
 5
5
1 0
1 5
2 0
Notice that the function is periodic and repeats every 2π.
As can be found from L’Hospital’s Rule, the amplitude of the primary peak depends on N:
amplitude = Ntot/sqrt(2π)
The first zero (a measure of the width of the primary peak) is given by
0
2
first zero
totN t
π
ω =
3. Infinite comb function: Using the previous two equations, one can see that in the limit as Ntot → ∞, the
large peaks (like the ones at –2π, 0, and 2π) get infinitely tall and infinitely narrow. They are delta
functions! Thus, the Fourier transform of an infinite comb function in the time domain, is a similar
infinite comb function in the frequency domain.
Delta functions – pg 5
FT(comb) plotted here as a
function of ωt0, for Ntot = 21,
without the 1/sqrt(2π)